Environmental DNA metabarcoding of benthic bacterial communities indicates the benthic footprint of salmon aquaculture

Exploring the Microbial Mosaic: Insights into Composition, Diversity, and Environmental Drivers in the Pearl River Estuary Sediments

River estuaries are dynamic and complex ecosystems influenced by various natural processes, including climatic fluctuations and anthropogenic activities. The Pearl River Estuary (PRE), one of the largest in China, receives significant land-based pollutants due to its proximity to densely populated areas and urban development. This study aimed to characterize the composition, diversity, and distribution patterns of sediment microbial communities (bacteria, archaea, and eukaryotes) and investigated the connection with environmental parameters within the PRE and adjacent shelf. Physicochemical conditions, such as oxygen levels, nitrogen compounds, and carbon content, were analyzed. The study found that the microbial community structure was mainly influenced by site location and core depth, which explained approximately 67% of the variation in each kingdom. Sites and core depths varied in sediment properties such as organic matter content and redox conditions, leading to distinct microbial groups associated with specific chemical properties of the sediment, notably C/N ratio and NH4+ concentration. Despite these differences, certain dominant taxonomic groups were consistently present across all sites: Gammaproteobacteria in bacteria; Bathyarchaeia, Nitrososphaeria, and Thermoplasmata in archaea; and SAR in Eukaryota. The community diversity index was the highest in the bacteria kingdom, while the lowest values were observed at site P03 across the three kingdoms and were significantly different from all other sites. Overall, this study highlights the effect of depth, core depth, and chemical properties on sediment microbiota composition. The sensitivity and dynamism of the microbiota, along with the possibility of identifying specific markers for changes in environmental conditions, is valuable for managing and preserving the health of estuaries and coastal ecosystems.

Geographical variation of bacterial and ciliophoran communities in tidal flats in a continental archipelago

In tidal flats, which are located at the transition zone between terrestrial and marine ecosystems, environmental factors such as temperature, sediment particle size, and tidal range exhibit geographic variation. Accordingly, the composition and structure of the microbial communities in the tidal flats are likely to vary in geographically different habitats. To clarify these differences with environmental factors causing them, we analyzed microbial communities consisting of bacteria and ciliates in sediments collected from nine tidal flats in geographical diverse region from Hokkaido to Kagoshima, Japan. The results confirmed that the community structures of bacteria and ciliophora in tidal flat sediments differed at the geographical scale of the Japanese archipelago. However, the variation could not be explained by the physical distance between the tidal flats nor by the differences in the trophic conditions among the tidal flats. Instead, the OTU richness of both the bacterial and ciliophoran communities was significantly related to the tidal range. The results also showed that bacteria and ciliophora tended to form similar communities among the tidal flats with similar median particle sizes. Furthermore, ciliophoran communities were similar among the tidal flats with similar bacterial communities. The results suggest that bacteria and ciliophora interact each other through trophic relationships or physical and chemical processes in the sediment habitats.

Maximising environmental pressure-response relationship signals from diatom-based metabarcoding in rivers

DNA metabarcoding has been performed on a large number of river phytobenthos samples collected from the UK, using rbcL primers optimised for diatoms. Within this dataset the composition of non-diatom sequence reads was studied and the effect of including these in models for evaluating the nutrient gradient was assessed. Whilst many non-diatom taxonomic groups were detected, few contained the full diversity expected in riverine environments. This may be due to the performance of the current primers in characterising the wider phytobenthic community and influenced by the sampling method employed, as both were developed specifically for diatoms. Nevertheless, the study identified considerable diversity in some groups, e.g. Eustigmatophyceae and a wider distribution than previously thought for freshwater Phaeophyceae. These results offer a strong case for the benefits of metabarcoding for expanding knowledge of aquatic biodiversity in the UK and elsewhere. Many of the ASVs associated with non-diatoms showed significant pressure responses; however, models that included non-diatoms had similar predictive strength to those based on diatoms alone. Whilst limitations of the primers for assessing non-diatoms may play a role in explaining these results, the diatoms provide a strong signal along the nutrient gradient and other algae, therefore, add little unique information. We recommend that future developments should use ASVs to calculate metrics, with links to reference databases made as a final step to generate lists of taxa to support interpretation. Any further exploration of the potential of non-diatoms would benefit from access to a well-curated reference database, similar to diat.barcode. Such a database does not yet exist, and we caution against the indiscriminate use of NCBI GenBank as a taxonomic resource as many rbcL sequences deposited have not been curated.

Using eDNA to survey amphibians: Methods, applications, and challenges

In recent years, environmental DNA (eDNA) has received attention from biologists due to its sensitivity, convenience, labor and material efficiency, and lack of damage to organisms. The extensive application of eDNA has opened avenues for the monitoring and biodiversity assessment of amphibians, which are frequently small and difficult to observe in the field, in areas such as biodiversity survey assessment and detection of specific, rare and threatened, or alien invasive species. However, the accuracy of eDNA can be influenced by factors such as ambient temperature, pH, and false positives or false negatives, which makes eDNA an adjunctive tool rather than a replacement for traditional surveys. This review provides a concise overview of the eDNA method and its workflow, summarizes the differences between applying eDNA for detecting amphibians and other organisms, reviews the research progress in eDNA technology for amphibian monitoring, identifies factors influencing detection efficiency, and discusses the challenges and prospects of eDNA. It aims to serve as a reference for future research on the application of eDNA in amphibian detection.

Descriptive analyses of bacterial communities in marine sediment microcosms spiked with fish wastes, emamectin benzoate, and oxytetracycline

In marine sediments surrounding salmon aquaculture sites, organic matter (OM) enrichment has been shown to influence resident bacterial community composition; however, additional effects on these communities due to combined use of the sea-lice therapeutant emamectin benzoate (EMB) and the widely used antibiotic oxytetracycline (OTC) are unknown. Here, we use sediment microcosms to assess the influence of OM, EMB, and OTC on benthic bacterial communities. Microcosms consisted of mud or sand sediments enriched with OM (fish and feed wastes) and spiked with EMB and OTC at environmentally-relevant concentrations. Samples were collected from initial matrices at the initiation of the trial and after 110 days for 16 S rRNA gene sequencing of the V3-V4 region and microbiome profiling. The addition of OM in both mud and sand sediments reduced alpha diversities; for example, an average of 1106 amplicon sequence variants (ASVs) were detected in mud with no OM addition, while only 729 and 596 ASVs were detected in mud with low OM and high OM, respectively. Sediments enriched with OM had higher relative abundances of Spirochaetota, Firmicutes, and Bacteroidota. For instance, Spirochaetota were detected in sediments with no OM with a relative abundance range of 0.01-1.2%, while in sediments enriched with OM relative abundance varied from 0.16% to 26.1%. In contrast, the addition of EMB (60 ng/g) or OTC (150 ng/g) did not result in distinct taxonomic shifts in the bacterial communities compared to un-spiked sediments during the timeline of this experiment. EMB and OTC concentrations may have been below effective inhibitor concentrations for taxa in these communities; further work should explore gene content and the presence of antibiotic resistance genes (ARGs) in sediment-dwelling bacteria.

A combination of machine-learning and eDNA reveals the genetic signature of environmental change at the landscape levels

The current advances of environmental DNA (eDNA) bring profound changes to ecological monitoring and provide unique insights on the biological diversity of ecosystems. The very nature of eDNA data is challenging yet also revolutionizing how biological monitoring information is analysed. In particular, new metrics and approaches should take full advantage of the extent and detail of molecular data produced by genetic methods. In this perspective, machine learning algorithms are particularly promising as they can capture complex relationships between the multiple environmental pressures and the diversity of biological communities. We investigated the potential of a new generation of biomonitoring tools that implement machine-learning techniques to fully exploit eDNA datasets. We trained a machine learning model to discriminate between reference and impacted communities of freshwater macroinvertebrates and assessed its performances using a large eDNA dataset collected at 64 standard federal monitoring sites across Switzerland. We show that a model trained on eDNA is significantly better than a naive model and performs similarly to a model trained on traditional data. Our proof-of-concept shows that such a combination of eDNA and machine learning approaches has the potential to complement or even replace traditional environmental monitoring, and could be scaled along temporal or spatial dimensions.

Core species and interactions prominent in fish-associated microbiome dynamics

BACKGROUND

In aquatic ecosystems, the health and performance of fish depend greatly on the dynamics of microbial community structure in the background environment. Nonetheless, finding microbes with profound impacts on fish's performance out of thousands of candidate species remains a major challenge.

METHODS

We examined whether time-series analyses of microbial population dynamics could illuminate core components and structure of fish-associated microbiomes in the background (environmental) water. By targeting eel-aquaculture-tank microbiomes as model systems, we reconstructed the population dynamics of the 9605 bacterial and 303 archaeal species/strains across 128 days.

RESULTS

Due to the remarkable increase/decrease of constituent microbial population densities, the taxonomic compositions of the microbiome changed drastically through time. We then found that some specific microbial taxa showed a positive relationship with eels' activity levels even after excluding confounding effects of environmental parameters (pH and dissolved oxygen level) on population dynamics. In particular, a vitamin-B₁₂-producing bacteria, Cetobacterium somerae, consistently showed strong positive associations with eels' activity levels across the replicate time series of the five aquaculture tanks analyzed. Network theoretical and metabolic modeling analyses further suggested that the highlighted bacterium and some other closely-associated bacteria formed "core microbiomes" with potentially positive impacts on eels.

CONCLUSIONS

Overall, these results suggest that the integration of microbiology, ecological theory, and network science allows us to explore core species and interactions embedded within complex dynamics of fish-associated microbiomes.  Video Abstract.

Environmental DNA-based profiling of benthic bacterial and eukaryote communities along a crude oil spill gradient in a coral reef in the Persian Gulf

Coral reef ecosystems in the Persian Gulf are frequently exposed to crude oil spills. We investigated benthic bacterial and eukaryote community structures at such coral reef sites subjected to different degrees of polycyclic aromatic hydrocarbon (PAH) pollution using environmental DNA (eDNA) metabarcoding. Both bacterial and eukaryote communities responded with pronounced shifts to crude oil pollution and distinguished control sites, moderately and heavily impacted sites with significant confidentiality. The observed community patterns were predominantly driven by Alphaproteobacteria and metazoans. Among these, we identified individual genera that were previously linked to oil spill stress, but also taxa, for which a link to hydrocarbon still remains to be established. Considering the lack of an early-warning system for the environmental status of coral reef ecosystems exposed to frequent crude-oil spills, our results encourage further research towards the development of an eDNA-based biomonitoring tool that exploits benthic bacterial and eukaryote communities as bioindicators.

Composition and functionality of bacterioplankton communities in marine coastal zones adjacent to finfish aquaculture

Finfish aquaculture is a fast-growing primary industry and is increasingly common in coastal ecosystems. Bacterioplankton is ubiquitous in marine environment and respond rapidly to environmental changes. Changes in bacterioplankton community are not well understood in semi-enclosed stratified embayments. This study aims to examine aquaculture effects in the composition and functional profiles of the bacterioplankton community using amplicon sequencing along a distance gradient from two finfish leases in a marine embayment. Results revealed natural stratification in bacterioplankton associated to NOx, conductivity, salinity, temperature and PO₄. Among the differentially abundant bacteria in leases, we found members associated with nutrient enrichment and aquaculture activities. Abundant predicted functions near leases were assigned to organic matter degradation, fermentation, and antibiotic resistance. This study provides a first effort to describe changes in the bacterioplankton community composition and function due to finfish aquaculture in a semi-enclosed and highly stratified embayment with a significant freshwater input.

Fine-scale differences in eukaryotic communities inside and outside salmon aquaculture cages revealed by eDNA metabarcoding

Aquaculture impacts on marine benthic ecosystems are widely recognized and monitored. However, little is known about the community changes occurring in the water masses surrounding aquaculture sites. In the present study, we studied the eukaryotic communities inside and outside salmonid aquaculture cages through time to assess the community changes in the neighbouring waters of the farm. Water samples were taken biweekly over five months during the production phase from inside the cages and from nearby points located North and South of the salmon farm. Eukaryotic communities were analyzed by eDNA metabarcoding of the partial COI Leray-XT fragment. The results showed that eukaryotic communities inside the cages were significantly different from those in the outside environment, with communities inside the cages having higher diversity values and more indicator species associated with them. This is likely explained by the appearance of fouling species that colonize the artificial structures, but also by other species that are attracted to the cages by other means. Moreover, these effects were highly localized inside the cages, as the communities identified outside the cages, both North and South, had very similar eukaryotic composition at each point in time. Overall, the eukaryotic communities, both inside and outside the cages, showed similar temporal fluctuations through the summer months, with diversity peaks occurring at the end of July, beginning of September, and in the beginning of November, with the latter showing the highest Shannon diversity and richness values. Hence, our study suggests that seasonality, together with salmonid aquaculture, are the main drivers of eukaryotic community structure in surface waters surrounding the farm.

Developing Indicators of Nutrient Pollution in Streams Using 16S rRNA Gene Metabarcoding of Periphyton-Associated Bacteria

Indicators based on nutrient-biota relationships in streams can inform water quality restoration and protection programs. Bacterial assemblages could be particularly useful indicators of nutrient effects because they are species-rich, important contributors to ecosystem processes in streams, and responsive to rapidly changing conditions. Here, we sampled 25 streams weekly (12-14 times each) and used 16S rRNA gene metabarcoding of periphyton-associated bacteria to quantify the effects of total phosphorus (TP) and total nitrogen (TN). Threshold indicator taxa analysis identified assemblage-level changes and amplicon sequence variants (ASVs) that increased or decreased with increasing TP and TN concentrations (i.e., low P, high P, low N, and high N ASVs). Boosted regression trees confirmed that relative abundances of gene sequence reads for these four indicator groups were associated with nutrient concentrations. Gradient forest analysis complemented these results by using multiple predictors and random forest models for each ASV to identify portions of TP and TN gradients at which the greatest changes in assemblage structure occurred. Synthesized statistical results showed bacterial assemblage structure began changing at 24 μg TP/L with the greatest changes occurring from 110 to 195 μg/L. Changes in the bacterial assemblages associated with TN gradually occurred from 275 to 855 μg/L. Taxonomic and phylogenetic analyses showed that low nutrient ASVs were commonly Firmicutes, Verrucomicrobiota, Flavobacteriales, and Caulobacterales, Pseudomonadales, and Rhodobacterales of Proteobacteria, whereas other groups, such as Chitinophagales of Bacteroidota, and Burkholderiales, Rhizobiales, Sphingomonadales, and Steroidobacterales of Proteobacteria comprised the high nutrient ASVs. Overall, the responses of bacterial ASV indicators in this study highlight the utility of metabarcoding periphyton-associated bacteria for quantifying biotic responses to nutrient inputs in streams.

Environmental DNA metabarcoding for benthic monitoring: A review of sediment sampling and DNA extraction methods

Environmental DNA (eDNA) metabarcoding (parallel sequencing of DNA/RNA for identification of whole communities within a targeted group) is revolutionizing the field of aquatic biomonitoring. To date, most metabarcoding studies aiming to assess the ecological status of aquatic ecosystems have focused on water eDNA and macroinvertebrate bulk samples. However, the eDNA metabarcoding has also been applied to soft sediment samples, mainly for assessing microbial or meiofaunal biota. Compared to classical methodologies based on manual sorting and morphological identification of benthic taxa, eDNA metabarcoding offers potentially important advantages for assessing the environmental quality of sediments. The methods and protocols utilized for sediment eDNA metabarcoding can vary considerably among studies, and standardization efforts are needed to improve their robustness, comparability and use within regulatory frameworks. Here, we review the available information on eDNA metabarcoding applied to sediment samples, with a focus on sampling, preservation, and DNA extraction steps. We discuss challenges specific to sediment eDNA analysis, including the variety of different sources and states of eDNA and its persistence in the sediment. This paper aims to identify good-practice strategies and facilitate method harmonization for routine use of sediment eDNA in future benthic monitoring.

Evaluating eDNA for Use within Marine Environmental Impact Assessments

In this review, the use of environmental DNA (eDNA) within Environmental Impact Assessment (EIA) is evaluated. EIA documents provide information required by regulators to evaluate the potential impact of a development project. Currently eDNA is being incorporated into biodiversity assessments as a complementary method for detecting rare, endangered or invasive species. However, questions have been raised regarding the maturity of the field and the suitability of eDNA information as evidence for EIA. Several key issues are identified for eDNA information within a generic EIA framework for marine environments. First, it is challenging to define the sampling unit and optimal sampling strategy for eDNA with respect to the project area and potential impact receptor. Second, eDNA assay validation protocols are preliminary at this time. Third, there are statistical issues around the probability of obtaining both false positives (identification of taxa that are not present) and false negatives (non-detection of taxa that are present) in results. At a minimum, an EIA must quantify the uncertainty in presence/absence estimates by combining series of Bernoulli trials with ad hoc occupancy models. Finally, the fate and transport of DNA fragments is largely unknown in environmental systems. Shedding dynamics, biogeochemical and physical processes that influence DNA fragments must be better understood to be able to link an eDNA signal with the receptor’s state. The biggest challenge is that eDNA is a proxy for the receptor and not a direct measure of presence. Nonetheless, as more actors enter the field, technological solutions are likely to emerge for these issues. Environmental DNA already shows great promise for baseline descriptions of the presence of species surrounding a project and can aid in the identification of potential receptors for EIA monitoring using other methods.

Environmental DNA metabarcoding reveals comparable responses to agricultural stressors on different trophic levels of a freshwater community

Freshwater habitats are under stress from agricultural land use, most notably the influx of neonicotinoid pesticides and increased nutrient pressure from fertilizer. Traditional studies investigating the effects of stressors on freshwater systems are often limited to a narrow range of taxa, depending heavily on morphological expertise. Additionally, disentanglement of multiple simultaneous stressors can be difficult in field studies, whereas controlled laboratory conditions do not accurately reflect natural conditions and food webs. To overcome these drawbacks, we investigated the impacts of two agricultural stressors (the neonicotinoid insecticide thiacloprid and fertilizer) in full‐factorial design in a semi‐natural research site, using environmental DNA sampling to study three different taxonomic groups representing three trophic levels: bacteria (decomposers), phytoplankton (primary producers), and chironomids (consumers). The results show considerable impact of both stressors across trophic levels, with an additive effect of fertilizer and thiacloprid on community composition at all levels. These findings suggest that agricultural stressors affect the entire food web, either directly or through cascade reactions. They are also consistent with morphological assessments that were performed in the same study site, even at a lower number of replicates. The study presented shows that the use of multimarker environmental DNA provides a more comprehensive assessment of stressor impacts across multiple trophic levels, at a higher taxonomic resolution than traditional surveys. Additionally, many putative novel bioindicators for both agricultural stressors were discovered. We encourage further investigations into stressors impacts at different trophic levels, which will lead to more effective monitoring and management of freshwater systems.

Comparing sediment preservation methods for genomic biomonitoring of coastal marine ecosystems

To avoid loss of genetic information in environmental DNA (eDNA) field samples, the preservation of nucleic acids during field sampling is a critical step. In the development of standard operating procedures (SOPs) for eDNA-based compliance monitoring, the effect of different routinely used sediment preservations on biological community structures serving as bioindicators has gone untested. We compared eDNA metabarcoding results of marine bacterial communities from sample aliquots that were treated with a nucleic acid preservation solution (treated samples) and aliquots that were frozen without further treatment (non-treated samples). Sediment samples were obtained from coastal locations subjected to different stressors (aquaculture, urbanization, industry). DNA extraction efficiency, bacterial community profiles, and measures of alpha- and beta-diversity were highly congruent between treated and non-treated samples. As both preservation methods provide the same relevant information to environmental managers and regulators, we recommend the inclusion of both methods into SOPs for biomonitoring in marine coastal environments.

Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or "in development", hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (a) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (b) De novo bioindicator analyses; (c) Structural community metrics including inferred ecological networks; and (d) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programmes that leverage recent analytical advancements, while pointing out current limitations and future research needs.

Global Trends of Benthic Bacterial Diversity and Community Composition Along Organic Enrichment Gradients of Salmon Farms

The analysis of benthic bacterial community structure has emerged as a powerful alternative to traditional microscopy-based taxonomic approaches to monitor aquaculture disturbance in coastal environments. However, local bacterial diversity and community composition vary with season, biogeographic region, hydrology, sediment texture, and aquafarm-specific parameters. Therefore, without an understanding of the inherent variation contained within community complexes, bacterial diversity surveys conducted at individual farms, countries, or specific seasons may not be able to infer global universal pictures of bacterial community diversity and composition at different degrees of aquaculture disturbance. We have analyzed environmental DNA (eDNA) metabarcodes (V3-V4 region of the hypervariable SSU rRNA gene) of 138 samples of different farms located in different major salmon-producing countries. For these samples, we identified universal bacterial core taxa that indicate high, moderate, and low aquaculture impact, regardless of sampling season, sampled country, seafloor substrate type, or local farming and environmental conditions. We also discuss bacterial taxon groups that are specific for individual local conditions. We then link the metabolic properties of the identified bacterial taxon groups to benthic processes, which provides a better understanding of universal benthic ecosystem function(ing) of coastal aquaculture sites. Our results may further guide the continuing development of a practical and generic bacterial eDNA-based environmental monitoring approach.

A step towards the validation of bacteria biotic indices using DNA metabarcoding for benthic monitoring

Environmental genomics is a promising field for monitoring biodiversity in a timely fashion. Efforts have increasingly been dedicated to the use of bacteria DNA derived data to develop biotic indices for benthic monitoring. However, a substantial debate exists about whether bacteria-derived data using DNA metabarcoding should follow, for example, a taxonomy-based or a taxonomy-free approach to marine bioassessments. Here, we showcase the value of DNA-based monitoring using the impact of fish farming as an example of anthropogenic disturbances in coastal areas and compare the performance of taxonomy-based and taxonomy-free approaches in detecting environmental alterations. We analysed samples collected near to the farm cages and along distance gradients from two aquaculture installations, and at control sites, to evaluate the effect of this activity on bacterial assemblages. Using the putative response of bacterial taxa to stress we calculated the taxonomy-based biotic index microgAMBI. The distribution of individual amplicon sequence variants (ASVs), as a function of a gradient in sediment acid volatile sulphides, was then used to derive a taxonomy-free bacterial biotic index specific for this data set using a de novo approach based on quantile regression splines. Our results show that microgAMBI revealed a organically enriched environment along the gradient. However, the de novo biotic index outperformed microgAMBI by providing a higher discriminatory power in detecting changes in abiotic factors directly related to fish production, whilst allowing the identification of new ASVs bioindicators. The de novo strategy applied here represents a robust method to define new bioindicators in regions or habitats where no previous information about the response of bacteria to environmental stressors exists.

Identifying the minimum amplicon sequence depth to adequately predict classes in eDNA-based marine biomonitoring using supervised machine learning

Environmental DNA metabarcoding is a powerful approach for use in biomonitoring and impact assessments. Amplicon-based eDNA sequence data are characteristically highly divergent in sequencing depth (total reads per sample) as influenced inter alia by the number of samples simultaneously analyzed per sequencing run. The random forest (RF) machine learning algorithm has been successfully employed to accurately classify unknown samples into monitoring categories. To employ RF to eDNA data, and avoid sequencing-depth artifacts, sequence data across samples are normalized using rarefaction, a process that inherently loses information. The aim of this study was to inform future sampling designs in terms of the relationship between sampling depth and RF accuracy. We analyzed three published and one new bacterial amplicon datasets, using a RF, based initially on the maximal rarefied data available (minimum mean of > 30,000 reads across all datasets) to give our baseline performance. We then evaluated the RF classification success based on increasingly rarefied datasets. We found that extreme to moderate rarefaction (50-5000 sequences per sample) was sufficient to achieve prediction performance commensurate to the full data, depending on the classification task. We did not find that the number of classification classes, data balance across classes, or the total number of sequences or samples, were associated with predictive accuracy. We identified the ability of the training data to adequately characterize the classes being mapped as the most important criterion and discuss how this finding can inform future sampling design for eDNA based biomonitoring to reduce costs and computation time.

Environmental DNA metabarcoding reveals estuarine benthic community response to nutrient enrichment - Evidence from an in-situ experiment

Nutrient loading is a major threat to estuaries and coastal environments worldwide, therefore, it is critical that we have good monitoring tools to detect early signs of degradation in these ecologically important and vulnerable ecosystems. Traditionally, bottom-dwelling macroinvertebrates have been used for ecological health assessment but recent advances in environmental genomics mean we can now characterize less visible forms of biodiversity, offering a more holistic view of the ecosystem and potentially providing early warning signals of disturbance. We carried out a manipulative nutrient enrichment experiment (0, 150 and 600 g N fertilizer m^-2) in two estuaries in New Zealand to assess the effects of nutrient loading on benthic communities. After seven months of enrichment, environmental DNA (eDNA) metabarcoding was used to examine the response of eukaryotic (18S rRNA), diatom only (rbcL) and bacterial (16S rRNA) communities. Multivariate analyses demonstrated changes in eukaryotic, diatom and bacterial communities in response to nutrient enrichment at both sites, despite differing environmental conditions. These patterns aligned with changes in macrofaunal communities identified using traditional morphological techniques, confirming concordance between disturbance indicators detected by eDNA and current monitoring approaches. Clear shifts in eukaryotic and bacterial indicator taxa were seen in response to nutrient loading while changes in diatom only communities were more subtle. Community changes were discernible between 0 and 150 g N m^-2 treatments, suggesting that estuary health assessment tools could be developed to detect early signs of degradation. Increasing variation in community structure associated with nutrient loading could also be used as an indicator of stress or approaching tipping points. This work represents a first step towards the development of molecular-based estuary monitoring tools, which could provide a more holistic and standardized approach to ecosystem health assessment with faster turn-around times and lower costs.

Assessment of microbial plankton diversity as an ecological indicator in the NW Mediterranean coast

High-throughput sequencing of microbial assemblages has been proposed as an alternative methodology to the traditional ones used in marine monitoring and environmental assessment. Here, we evaluated pico- and nanoplankton diversity as ecological indicators in NW Mediterranean coastal waters by comparing their diversity in samples subjected to varying degrees of continental pressures. Using metabarcoding of the 16S and 18S rRNA genes, we explored whether alphadiversity indices, abundance of Operational Taxonomic Units and taxonomic groups (and their ratios) provide information on the ecological quality of coastal waters. Our results revealed that only eukaryotic diversity metrics and a limited number of prokaryotic and eukaryotic taxa displayed potential in assessing continental influences in our surveyed area, resulting thus in a restrained potential of microbial plankton diversity as an ecological indicator. Therefore, incorporating microbial plankton diversity in environmental assessment could not always result in a significant improvement of current marine monitoring strategies.

Comparing sediment DNA extraction methods for assessing organic enrichment associated with marine aquaculture

Marine sediments contain a high diversity of micro- and macro-organisms which are important in the functioning of biogeochemical cycles. Traditionally, anthropogenic perturbation has been investigated by identifying macro-organism responses along gradients. Environmental DNA (eDNA) analyses have recently been advocated as a rapid and cost-effective approach to measuring ecological impacts and efforts are underway to incorporate eDNA tools into monitoring. Before these methods can replace or complement existing methods, robustness and repeatability of each analytical step has to be demonstrated. One area that requires further investigation is the selection of sediment DNA extraction method. Environmental DNA sediment samples were obtained along a disturbance gradient adjacent to a Chinook (Oncorhynchus tshawytscha) salmon farm in Otanerau Bay, New Zealand. DNA was extracted using four extraction kits (Qiagen DNeasy PowerSoil, Qiagen DNeasy PowerSoil Pro, Qiagen RNeasy PowerSoil Total RNA/DNA extraction/elution and Favorgen FavorPrep Soil DNA Isolation Midi Kit) and three sediment volumes (0.25, 2, and 5 g). Prokaryotic and eukaryotic communities were amplified using primers targeting the 16S and 18S ribosomal RNA genes, respectively, and were sequenced on an Illumina MiSeq. Diversity and community composition estimates were obtained from each extraction kit, as well as their relative performance in established metabarcoding biotic indices. Differences were observed in the quality and quantity of the extracted DNA amongst kits with the two Qiagen DNeasy PowerSoil kits performing best. Significant differences were observed in both prokaryotes and eukaryotes (p < 0.001) richness among kits. A small proportion of amplicon sequence variants (ASVs) were shared amongst the kits (~3%) although these shared ASVs accounted for the majority of sequence reads (prokaryotes: 59.9%, eukaryotes: 67.2%). Differences were observed in the richness and relative abundance of taxonomic classes revealed with each kit. Multivariate analysis showed that there was a significant interaction between "distance" from the farm and "kit" in explaining the composition of the communities, with the distance from the farm being a stronger determinant of community composition. Comparison of the kits against the bacterial and eukaryotic metabarcoding biotic index suggested that all kits showed similar patterns along the environmental gradient. Overall, we advocate for the use of Qiagen DNeasy PowerSoil kits for use when characterizing prokaryotic and eukaryotic eDNA from marine farm sediments. We base this conclusion on the higher DNA quality values and richness achieved with these kits compared to the other kits/amounts investigated in this study. The additional advantage of the PowerSoil Kits is that DNA extractions can be performed using an extractor robot, offering additional standardization and reproducibility of results.

A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay

Routine monitoring of benthic biodiversity is critical for managing and understanding the anthropogenic impacts on marine, transitional and freshwater ecosystems. However, traditional reliance on morphological identification generally makes it cost-prohibitive to increase the scale of monitoring programmes. Metabarcoding of environmental DNA has clear potential to overcome many of the problems associated with traditional monitoring, with prokaryotes and other microorganisms showing particular promise as bioindicators. However, due to the limited knowledge regarding the ecological roles and responses of environmental microorganisms to different types of pressure, the use of de novo approaches is necessary. Here, we use two such approaches for the prediction of multiple impacts present in estuaries and coastal areas of the Bay of Biscay based on microbial communities. The first (Random Forests) is a machine learning method while the second (Threshold Indicator Taxa Analysis and quantile regression splines) is based on de novo identification of bioindicators. Our results show that both methods overlap considerably in the indicator taxa identified, but less for sequence variants. Both methods also perform well in spite of the complexity of the studied ecosystem, providing predictive models with strong correlation to reference values and fair to good agreement with ecological status groups. The ability to predict several specific types of pressure is especially appealing. The cross-validated models and biotic indices developed can be directly applied to predict the environmental status of estuaries in the same geographical region, although more work is needed to evaluate and improve them for use in new regions or habitats.

Supervised machine learning is superior to indicator value inference in monitoring the environmental impacts of salmon aquaculture using eDNA metabarcodes

Increasing anthropogenic impact and global change effects on natural ecosystems has prompted the development of less expensive and more efficient bioassessments methodologies. One promising approach is the integration of DNA metabarcoding in environmental monitoring. A critical step in this process is the inference of ecological quality (EQ) status from identified molecular bioindicator signatures that mirror environmental classification based on standard macroinvertebrate surveys. The most promising approaches to infer EQ from biotic indices (BI) are supervised machine learning (SML) and the calculation of indicator values (IndVal). In this study we compared the performance of both approaches using DNA metabarcodes of bacteria and ciliates as bioindicators obtained from 152 samples collected from seven Norwegian salmon farms. Results from standard macroinvertebrate-monitoring of the same samples were used as reference to compare the accuracy of both approaches. First, SML outperformed the IndVal approach to infer EQ from eDNA metabarcodes. The Random Forest (RF) algorithm appeared to be less sensitive to noisy data (a typical feature of massive environmental sequence data sets) and uneven data coverage across EQ classes (a typical feature of environmental compliance monitoring scheme) compared to a widely used method to infer IndVals for the calculation of a BI. Second, bacteria allowed for a more accurate EQ assessment than ciliate eDNA metabarcodes. For the implementation of DNA metabarcoding into routine monitoring programmes to assess EQ around salmon aquaculture cages, we therefore recommend bacterial DNA metabarcodes in combination with SML to classify EQ categories based on molecular signatures.

Mixed-habitat assimilation of organic waste in coastal environments - It's all about synergy!

Fish farms are increasingly situated in strong current sites above or near to mixed-bottom habitats that include organisms not normally considered in the context of organic enrichment. This study takes a holistic view of the benthic enrichment process by combining different survey techniques on complimentary spatial scales: conventional macrofaunal cores, larger-scale visual quantification of epibiota and environmental-DNA metabarcoding of microbial communities. A large tube forming polychaete (Arenicola marina), normally found intertidally and living too deep for conventional sampling, was observed occupying an opportunistic niche in areas of high deposition and in very close association with Capitellid worm complexes. The surface-dwelling brittlestar, Ophiocomina nigra, was abundant at distances of 250-1000 m from Farm-B, suggesting a positive response to enrichment, but was displaced where sedimentation exceed 5 g m² d^-1. A corresponding gradient was evident within the sediment microbial communities, supporting established theories about ecosystem engineering and multi-species synergies for organic waste assimilation. Many of the bacteria present in the near-farm sediments were linked to the farmed fish and fish health issues suggesting one or two-way inoculation pressures. These functionally different benthic organisms are intrinsically linked and the resulting synergy has the potential to assimilate significant quantities of anthropogenically produced organic waste contributing to environmental sustainability.

Substratum-associated microbiota

This survey of 2018 literature on substratum-associated microbiota presents brief highlights on research findings from primarily freshwaters, but includes those from a variety of aquatic ecosystems. Coverage of topics associated with benthic algae and cyanobacteria, though not comprehensive, includes new methods, taxa new to science, nutrient dynamics, trophic interactions, herbicides and other pollutants, metal contaminants, nuisance, bloom-forming and harmful algae, bioassessment, and bioremediation. Coverage of bacteria, also not comprehensive, focused on methylation of mercury, metal contamination, toxins, and other environmental pollutants, including oil, as well as the use of benthic bacteria as bioindicators, in bioassessment tools and in biomonitoring. Additionally, we cover trends in recent and emerging topics on substratum-associated microbiota of relevance to the Water Environment Federation. PRACTITIONER POINTS: This review of literature from 2018 on substratum-associated microbiota presents highlights of findings on algae, cyanobacteria, and bacteria from primarily freshwaters. Topics covered that focus on algae and cyanobacteria include findings on new methods, taxa new to science, nutrient dynamics, trophic interactions, herbicides and other pollutants, metal contaminants, nuisance, bloomforming and harmful algae, bioassessment, and bioremediation. Topics covered that focus on bacteria include findings on methylation of mercury, metal contamination, toxins and other environmental pollutants, including oil, as well as the us e of benthic bacteria as bioindicators, in bioassessment tools and in biomonitoring. A brief presentation of new, noteworthy and emerging topics on substratum-associated microbiota, build on those from 2017, to highlight those of particular relevance to the Water Environment Federation.

Archaeal community variation in the Qinhuangdao coastal aquaculture zone revealed by high-throughput sequencing

The differences in archaeal diversity and community composition in the sediments and waters of the Qinhuangdao coastal aquaculture zone were investigated. Furthermore, the associations between dominant archaeal taxa with geographic and environmental variables were evaluated. High-throughput sequencing of archaeal 16S rRNA genes yielded a total of 176,211 quality-filtered reads and 1,178 operational taxonomic units (OTUs) overall. The most abundant phylum and class among all communities were Thaumarchaeota and Nitrososphaeria, respectively. Beta diversity analysis indicated that community composition was divided into two groups according to the habitat type (i.e., sediments or waters). Only 9.8% OTUs were shared by communities from the two habitats, while 73.9% and 16.3% of the OTUs were unique to sediment or water communities, respectively. Furthermore, the relative abundances of the dominant OTUs differed with habitat type. Investigations of relationships between dominant OTUs and environmental variables indicated that some dominant OTUs were more sensitive to variation in environmental factors, which could be due to individual taxonomic differences in lifestyles and biological processes. Overall, the investigation of archaeal community variation within the Qinhuangdao coastal aquaculture zone provides an important baseline understanding of the microbial ecology in this important ecosystem.

Multi-marker eDNA metabarcoding survey to assess the environmental impact of three offshore gas platforms in the North Adriatic Sea (Italy)

The environmental DNA (eDNA) metabarcoding represents a new promising tool for biomonitoring and environmental impact assessment. One of the main advantages of eDNA metabarcoding, compared to the traditional morphotaxonomy-based methods, is to provide a more holistic biodiversity information that includes inconspicuous morphologically non-identifiable taxa. Here, we use eDNA metabarcoding to survey marine biodiversity in the vicinity of the three offshore gas platforms in North Adriatic Sea (Italy). We isolated eDNA from 576 water and sediment samples collected at 32 sampling sites situated along four axes at increasing distances from the gas platforms. We obtained about 46 million eDNA sequences for 5 markers from nuclear 18S V1V2, 18S V4, 18S 37F and mitochondrial 16S and COI genes that cover a wide diversity of benthic and planktonic eukaryotes. Our results showed some impact of platform activities on benthic and pelagic communities at very close distance (<50 m), while communities for intermediate (125 m, 250 m, 500 m) and reference (1000 m, 2000 m) sites did not show any particular biodiversity changes that could be related to platforms activities. The most significant community change along the distance gradient was obtained with the 18S V1V2 marker targeting benthic eukaryotes, even though other markers showed similar trends, but to a lesser extent. These results were congruent with the AMBI index inferred from the eDNA sequences assigned to benthic macrofauna. We finally explored the relation between various physicochemical parameters, including hydrocarbons, on benthic community in the case of one of the platforms. Our results showed that these communities were not significantly impacted by most of hydrocarbons, but rather by macro-elements and sediment texture.

Metabarcoding and machine learning analysis of environmental DNA in ballast water arriving to hub ports

While ballast water has long been linked to the global transport of invasive species, little is known about its microbiome. Herein, we used 16S rRNA gene sequencing and metabarcoding to perform the most comprehensive microbiological survey of ballast water arriving to hub ports to date. In total, we characterized 41 ballast, 20 harbor, and 6 open ocean water samples from four world ports (Shanghai, China; Singapore; Durban, South Africa; Los Angeles, California). In addition, we cultured Enterococcus and E. coli to evaluate adherence to International Maritime Organization standards for ballast discharge. Five of the 41 vessels - all of which were loaded in China - did not comply with standards for at least one indicator organism. Dominant bacterial taxa of ballast water at the class level were Alphaproteobacteria, Gammaproteobacteria, and Bacteroidia. Ballast water samples were composed of significantly lower proportions of Oxyphotobacteria than either ocean or harbor samples. Linear discriminant analysis (LDA) effect size (LEfSe) and machine learning were used to identify and test potential biomarkers for classifying sample types (ocean, harbor, ballast). Eight candidate biomarkers were used to achieve 81% (k nearest neighbors) to 88% (random forest) classification accuracy. Further research of these biomarkers could aid the development of techniques to rapidly assess ballast water origin.

Temporal Bacterial Surveillance of Salmon Aquaculture Sites Indicates a Long Lasting Benthic Impact With Minimal Recovery

Coastal aquaculture has experienced substantial growth in the last few decades and associated impacts on natural environments are of increasing importance. Understanding both the effects of aquaculture on marine ecosystems and the processes of recovery during fallowing periods is crucial for the development of a more environmentally sustainable industry. Because bacteria are sensitive to environmental change, surveying fluctuations in bacterial communities is a promising tool for monitoring the status of benthic environments. Here, we used 16S rRNA gene high-throughput sequencing to characterize bacterial communities in flocculent matter samples collected over a period of 3 years and at various distances from cages (0–200 meters) at production and fallow (3–35 months) salmon aquaculture sites in southern Newfoundland to evaluate the environmental impact of aquaculture on predominantly hard-bottom substrates. Bacterial composition analysis revealed four clusters, three of which (defined as “recently disturbed,” “intermediate impact,” and “high impact”) differed markedly from a fourth “low impact” cluster that contained far-field samples collected >500 m from cages. Samples within the high impact group were most often collected directly under cages, whereas those in the intermediate impact group were mainly sampled from 20 to 40 m from cages. Large scale phylum shifts (increases of Bacteroidetes, Firmicutes, Spirochaetes, and decreases in Proteobacteria and Epsilonbacteraeota) and a decline in bacterial diversity were observed in the high impact cluster, indicating significant ecological change. Samples from sites of different fallow duration were found in the high impact cluster, indicating a lack of recovery, even after 35 months of fallowing. Finally, we identified 28 genera as bacterial biomarkers, specific to one or more clusters, including genera associated with organically enriched environments and previously reported in the context of aquaculture impacts. Tracking the relative abundance of biomarkers in relation to different lengths of fallowing in the three more impacted clusters showed that these markers remained significantly above low impact cluster levels at all times, further pointing toward incomplete recovery. Our results suggest that coastal aquaculture on hard-bottom substrates is prone to long lasting impacts on bacterial communities, especially below cages, and that effects can be accurately tracked using bacterial community profiles or specific biomarkers.

Interactive effects of multiple stressors revealed by sequencing total (DNA) and active (RNA) components of experimental sediment microbial communities

Coastal waterways are increasingly exposed to multiple stressors, e.g. contaminants that can be delivered via pulse or press exposures. Therefore, it is crucial that ecological impacts can be differentiated among stressors to manage ecosystem threats. We investigated microbial community development in sediments exposed to press and pulse stressors. Press exposures were created with in situ mesocosm sediments containing a range of 'metal' concentrations (sediment contaminated with multiple metal(loid)s) and organic enrichment (fertiliser), while the pulse exposure was simulated by a single dose of organic fertiliser. All treatments and exposure concentrations were crossed in a fully factorial field experiment. We used amplicon sequencing to compare the sensitivity of the 1) total (DNA) and active (RNA) component of 2) bacterial (16S rRNA) and eukaryotic (18S rRNA) communities to contaminant exposures. Overall microbial community change was greater when exposed to press than pulse stressors, with the bacterial community responding more strongly than the eukaryotes. The total bacterial community represents a more time-integrated measure of change and proved to be more sensitive to multiple stressors than the active community. Metals and organic enrichment treatments interacted such that the effect of metals was weaker when the sediment was organically enriched. Taxa-level analyses revealed that press enrichment resulted in potential functional changes, mainly involving nitrogen cycling. Furthermore, enrichment generally reduced the abundance of active eukaryotes in the sediment. As well as demonstrating interactive impacts of metals and organic enrichment, this study highlights the sensitivity of next-generation sequencing for ecosystem biomonitoring of interacting stressors and identifies opportunities for more targeted application.

The future of biotic indices in the ecogenomic era: Integrating (e)DNA metabarcoding in biological assessment of aquatic ecosystems

The bioassessment of aquatic ecosystems is currently based on various biotic indices that use the occurrence and/or abundance of selected taxonomic groups to define ecological status. These conventional indices have some limitations, often related to difficulties in morphological identification of bioindicator taxa. Recent development of DNA barcoding and metabarcoding could potentially alleviate some of these limitations, by using DNA sequences instead of morphology to identify organisms and to characterize a given ecosystem. In this paper, we review the structure of conventional biotic indices, and we present the results of pilot metabarcoding studies using environmental DNA to infer biotic indices. We discuss the main advantages and pitfalls of metabarcoding approaches to assess parameters such as richness, abundance, taxonomic composition and species ecological values, to be used for calculation of biotic indices. We present some future developments to fully exploit the potential of metabarcoding data and improve the accuracy and precision of their analysis. We also propose some recommendations for the future integration of DNA metabarcoding to routine biomonitoring programs.